Person:

Torriani, Martin

Background: Obesity is associated with a relative deficiency of growth hormone, which is predictive of greater visceral fat and markers of cardiovascular risk. The study’s purpose was to use recombinant human growth hormone (rhGH) as a physiologic probe to assess the effects of reversing obesity-related GH deficiency on body composition, cardiovascular risk markers, and insulin resistance. Methods: 22 obese girls 13–21 years old were followed for a randomized 6-month trial of rhGH vs. placebo/no treatment. At baseline and 6-months, DXA was performed for body composition, MRI to measure visceral, subcutaneous and total adipose tissue (VAT, SAT and TAT), and fasting blood drawn for IGF-1, inflammatory cardiovascular risk markers [soluble intercellular adhesion molecule (sICAM), high sensitivity CRP], lipids and HbA1C. An oral glucose tolerance test (OGTT) was performed. Twelve girls completed the 6-month visit. Baseline and mean 6-month change were compared between the groups using the Student t-test and the relationship between variables was determined through multiple regression analysis. Results: After 6-months, the rhGH group maintained IGF-1 levels, and had decreases in total cholesterol (p = 0.03), sICAM-1 (p = 0.04) and HbA1C (p = 0.03) compared to placebo/no treatment. The rhGH group trended towards greater decreases in LDL and 2-hour OGTT glucose. Glucose tolerance did not worsen with rhGH administration. Conclusions: Administering rhGH in small doses is able to stabilize IGF-1 levels in obesity. We have also shown that rhGH administration leads to an improvement in some markers of cardiovacular risk with without adversely affecting glucose tolerance. Trial registration Clinical Trial Registration Number: NCT01169103.

Objective: The purpose of this study was to test a newly developed DXA method for abdominal fat depot quantification in subjects with AN, normal weight, and obesity using CT as a gold standard. Design and Methods 135 premenopausal women (overweight/obese: n=89, normal-weight: n=27, AN: n=19); abdominal visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and total adipose tissue (TAT) areas determined on CT and DXA. Results: There were strong correlations between DXA and CT measurements of abdominal fat compartments in all groups with the strongest correlation coefficients in the normal-weight and overweight/obese groups. Correlations of DXA and CT VAT measurements were strongest in the obese group and weakest in the AN group. DXA abdominal fat depots were higher in all groups compared to CT, with the largest % mean difference in the AN group and smallest in the obese group. Conclusions: A new DXA technique is able to assess abdominal fat compartments including VAT in premenopausal women across a large weight spectrum However, DXA measurements of abdominal fat were higher than CT, and this percent bias was most pronounced in the AN subjects and decreased with increasing weight, suggesting that this technique may be more useful in obese individuals.

Purpose: To determine if CT density thresholds of osteoblastic bone lesions can be used to distinguish untreated osteoblastic metastases from enostoses. Materials and Methods: The study group comprised 62 patients (37 enostoses, 25 untreated osteoblastic metastases) with sclerotic bone lesions found on CT. Etiology of sclerotic lesions was assessed histologically or by clinical and imaging follow-up. None of the patients had prior treatment for metastases. The average and maximum densities in Hounsfield Units (HU) were measured. Receiver operating curve (ROC) analysis was performed to determine sensitivity, specificity, area under the ROC curve (AUC), confidence intervals (CI), and cutoff values of CT densities to differentiate metastases from enostoses. Interreader reproducibility was assessed using intraclass correlation coefficient (ICC) with 95% CI. Results: Mean and maximum CT densities of enostoses were 1190 ± 239 and 1323 ± 234 HU and of osteoblastic metastases were 654 ± 176 and 787 ± 194 HU, respectively. Using a cut-off of 885 HU for average density, AUC was 0.982, sensitivity was 95%, and specificity was 96%. Using a cut-off of 1058 HU for maximum CT density, AUC was 0.976, sensitivity was 95%, and specificity was 96%. Mean density ICC was 0.987 for enostoses and 0.81 for metastases. Maximum density ICC was 0.814 for enostoses and 0.980 for metastases. Conclusion: CT density measurements can be used to distinguish untreated osteoblastic metastases from enostoses. An average density of 885 HU and a maximum density of 1058 HU provide reliable thresholds below which a metastatic lesion is the favored diagnosis.

Purpose: Osseous metastases often undergo an osteoblastic response following chemotherapy also known as the “flare” phenomenon. The purpose of our study was to demonstrate the quantitative CT changes in density of osseous metastases before and after chemotherapy. Materials and Methods: Our study was IRB approved and HIPAA compliant. Our cohort consisted of 48 consecutive cancer patients with studies both before chemotherapy/at the time of diagnosis of osseous metastases and 14 ± 3 (12-20) months after the initiation of treatment 60 ±10 (range: 37-80) years, 26 F, 22 M). CT density of all lesions was measured by two fellowship trained MSK radiologists. The largest possible region of interest was selected to measure the average and maximum densities in Hounsfield Units (HU). If multiple lesions were present, the largest lesion was evaluated. Treatment effects were assessed using paired t-tests, using P < 0.05 as statistically significant. Intraclass correlation coefficient (ICC) was calculated for the two readers. Results: The distribution of primary tumors was as follows: breast (20/48, 42%), lung (10/48, 21%), prostate (5/48, 10%), pancreatic (5/48, 10%), renal (2/48, 4%), and other (6/48, 13%). The measured lesions were in the following locations: spine/sacrum (35/48, 73%), pelvis (10/48, 21%), sternum (3/48, 6%). The distribution of lesion types were as follows: lytic (14/48, 29%), blastic (25/48, 52%), and mixed lytic-blastic (9/48, 19%). Mean and maximum CT densities (Reader 1) of all metastases before chemotherapy treatment were 328 ± 206 HU and 580 ± 391 HU, respectively and after chemotherapy treatment were 511 ± 263 HU and 789 ± 439 HU, respectively. There was a significant increase in mean and maximum CT densities of metastases following chemotherapy for all lesions collectively but also when separated into lytic, blastic, and mixed lytic-blastic lesions (P < 0.05). ICC was almost perfect for average density and moderate to substantial for maximum density. Conclusion: Quantitative assessment of osseous metastatic disease using CT density measurements confirms a statistically significant increase in density 12-20 months after initiation of chemotherapy. Clinical Application: Measuring changes in CT density of osseous metastases may have a significant role in evaluating chemotherapy effect.